Studying at the University of Verona

A.A. 2016/2017

Academic calendar

Il calendario accademico riporta le scadenze, gli adempimenti e i periodi rilevanti per la componente studentesca, personale docente e personale dell'Università. Sono inoltre indicate le festività e le chiusure ufficiali dell'Ateneo.
L’anno accademico inizia il 1° ottobre e termina il 30 settembre dell'anno successivo.

Academic calendar

Course calendar

The Academic Calendar sets out the degree programme lecture and exam timetables, as well as the relevant university closure dates. For further information, please get in touch with Operational unit: Science and Engineering Teaching and Student Services Unit

Definition of lesson periods
Period From To
I sem. Oct 3, 2016 Jan 31, 2017
II sem. Mar 1, 2017 Jun 9, 2017
Exam sessions
Session From To
Sessione invernale Appelli d'esame Feb 1, 2017 Feb 28, 2017
Sessione estiva Appelli d'esame Jun 12, 2017 Jul 31, 2017
Sessione autunnale Appelli d'esame Sep 1, 2017 Sep 29, 2017
Degree sessions
Session From To
Sessione estiva Appelli di Laurea Jul 18, 2017 Jul 18, 2017
Sessione autunnale Appelli di laurea Nov 22, 2017 Nov 22, 2017
Sessione invernale Appelli di laurea Mar 20, 2018 Mar 20, 2018
Holidays
Period From To
Festa di Ognissanti Nov 1, 2016 Nov 1, 2016
Festa dell'Immacolata Concezione Dec 8, 2016 Dec 8, 2016
Vacanze di Natale Dec 23, 2016 Jan 8, 2017
Vacanze di Pasqua Apr 14, 2017 Apr 18, 2017
Anniversario della Liberazione Apr 25, 2017 Apr 25, 2017
Festa del Lavoro May 1, 2017 May 1, 2017
Festa della Repubblica Jun 2, 2017 Jun 2, 2017
Vacanze estive Aug 8, 2017 Aug 20, 2017

Exam calendar

The exam roll calls are centrally administered by the operational unit  Science and Engineering Teaching and Student Services Unit
Exam Session Calendar and Roll call enrolment sistema ESSE3 .If you forget your password to the online services, please contact the technical office in your Faculty.

Exam calendar

Per dubbi o domande Read the answers to the more serious and frequent questions - F.A.Q. Examination enrolment

Academic staff

B C D F G L M O P Q S U

Belussi Alberto

alberto.belussi@univr.it +39 045 802 7980

Bombieri Nicola

nicola.bombieri@univr.it +39 045 802 7094

Bonacina Maria Paola

mariapaola.bonacina@univr.it +39 045 802 7046

Bonnici Vincenzo

vincenzo.bonnici@univr.it +39 045 802 7045

Boscaini Maurizio

maurizio.boscaini@univr.it

Carra Damiano

damiano.carra@univr.it +39 045 802 7059

Combi Carlo

carlo.combi@univr.it 045 802 7985

Daffara Claudia

claudia.daffara@univr.it +39 045 802 7942

Dalla Preda Mila

mila.dallapreda@univr.it

Di Pierro Alessandra

alessandra.dipierro@univr.it +39 045 802 7971

Drago Nicola

nicola.drago@univr.it 045 802 7081

Fiorini Paolo

paolo.fiorini@univr.it 045 802 7963

Fummi Franco

franco.fummi@univr.it 045 802 7994

Giachetti Andrea

andrea.giachetti@univr.it +39 045 8027998

Giacobazzi Roberto

roberto.giacobazzi@univr.it +39 045 802 7995

Gobbi Bruno

bruno.gobbi@univr.it

Gregorio Enrico

Enrico.Gregorio@univr.it 045 802 7937

Lora Michele

michele.lora@univr.it

Marzola Pasquina

pasquina.marzola@univr.it 045 802 7816 (ufficio); 045 802 7614 (laboratorio)

Mastroeni Isabella

isabella.mastroeni@univr.it +39 045 802 7089

Menegaz Gloria

gloria.menegaz@univr.it +39 045 802 7024

Oliboni Barbara

barbara.oliboni@univr.it +39 045 802 7077

Posenato Roberto

roberto.posenato@univr.it +39 045 802 7967

Pravadelli Graziano

graziano.pravadelli@univr.it +39 045 802 7081

Quaglia Davide

davide.quaglia@univr.it +39 045 802 7811

Segala Roberto

roberto.segala@univr.it 045 802 7997

Spoto Nicola Fausto

fausto.spoto@univr.it +39 045 8027940

Study Plan

The Study Plan includes all modules, teaching and learning activities that each student will need to undertake during their time at the University. Please select your Study Plan based on your enrolment year.

TeachingsCreditsTAFSSD
6
A
(MAT/02)
12
A
(ING-INF/05)
6
A
(FIS/01)
6
A
(INF/01)
12
A
(INF/01)
English language competence-complete b1 level
6
E
-
TeachingsCreditsTAFSSD
12
B
(INF/01)
6
C
(FIS/01)
6
B
(ING-INF/05)
12
B
(ING-INF/05)
One course to be chosen among the following
TeachingsCreditsTAFSSD
12
B
(ING-INF/05)
One course to be chosen among the following
6
B
(INF/01)
6
B
(INF/01)
6
F
(-)
Prova finale
6
E
(-)

1° Anno

TeachingsCreditsTAFSSD
6
A
(MAT/02)
12
A
(ING-INF/05)
6
A
(FIS/01)
6
A
(INF/01)
12
A
(INF/01)
English language competence-complete b1 level
6
E
-

2° Anno

TeachingsCreditsTAFSSD
12
B
(INF/01)
6
C
(FIS/01)
6
B
(ING-INF/05)
12
B
(ING-INF/05)
One course to be chosen among the following

3° Anno

TeachingsCreditsTAFSSD
12
B
(ING-INF/05)
One course to be chosen among the following
6
B
(INF/01)
6
B
(INF/01)
6
F
(-)
Prova finale
6
E
(-)

Legend | Type of training activity (TTA)

TAF (Type of Educational Activity) All courses and activities are classified into different types of educational activities, indicated by a letter.




SPlacements in companies, public or private institutions and professional associations

Teaching code

4S00005

Coordinatore

Isabella Mastroeni

Credits

6

Scientific Disciplinary Sector (SSD)

INF/01 - INFORMATICS

Language of instruction

Italian

Period

I sem. dal Oct 3, 2016 al Jan 31, 2017.

Learning outcomes

The course covers standard principles and methods in theoretical computer science, notably in automata theory and computability.
The course aims at providing theoretical computer science and programming languages capabilities.
At the end of the course, the student will have to show: to know and understand advanced computer science notions; to be able to apply the acquired capabilities and knowledge for solving problems in its field of study; to be able to develop necessary expertise for affording the following studies with a sufficient degree of autonomy.

Program

The course requires the standard courses on Programming, Algorithms, Discrete mathematics and logic. It is introductory for the advanced courses in Complexity, Programming languages and Compilers, as well as for the courses in Security and Cryptography, Static Analysis and Protection, Artificial Intelligence, Automated Deduction, Semantics, Non-standard computational models.
The course is structured in two parts.

Automata and formal languages (28h):
Formal languages and grammars,
finite state automata and regular languages,
context-free languages, normal forms, Push-down automata,
Chomsky classification of formal languages.

Computability (34h):
intuitive notion of algorithm,
Turing analysis of computable functions, Turing machines and WHILE-programs,
Church thesis,
Goedelization, universality,
Theorem s-m-n, unsolvable problems and halting problem,
metaprogramming,
recursive and recursive enumerable sets,
Recursion theorems, Rice Theorem,
reducibility, complete, creative and productive sets.

Bibliografia

Reference texts
Author Title Publishing house Year ISBN Notes
N. Jones Computability and Complexity MIT Press 1997
John E. Hopcroft, Rajeev Motwani, Jeffrey D. Ullman Introduction to Automata Theory, Languages and Computation (Edizione 2) Addison-Wesley 2000 0201441241
Michael Sipser Introduction to the Theory of Computation PWS 1997 053494728X
H. Rogers Theory of recursive functions and effective computability MIT Press 1988

Examination Methods

Written exam in 4 sessions, with intermediate evaluation. The exams are scheduled as follows: 1 intermediate (written) evaluation during the course, 1 exam in the Extraordinary Session at the end of the course, 1 exam in the Summer Session and 1 exams in the Fall Session. Each exam is split into two parts which can be passed separately and the whole evaluation is obtained as the mathematical average of the two evaluations. The exam is passed if the average evaluation is greater or equal to 18/30. Each evaluation remains valid for the whole current academic year.

Mandatory oral exam for evaluation greater than 26.

The task of the written exam consists in verifying the comprehension of course contents and the capability to apply these contents in the resolution of exercises in which students have to mainly classify languages (regular or context free) and sets (recursive theory and completeness) by using the formal proof tools provided in the course.
The task of the oral exam is that of verify an advanced comprehension of the course contents allowing a critic analysis and a reprocessing of the studied notions and results. This comprehension may be verified also by asking theorems and proofs.

Tipologia di Attività formativa D e F

Course not yet included

Career prospects


Avvisi degli insegnamenti e del corso di studio

Per la comunità studentesca

Se sei già iscritta/o a un corso di studio, puoi consultare tutti gli avvisi relativi al tuo corso di studi nella tua area riservata MyUnivr.
In questo portale potrai visualizzare informazioni, risorse e servizi utili che riguardano la tua carriera universitaria (libretto online, gestione della carriera Esse3, corsi e-learning, email istituzionale, modulistica di segreteria, procedure amministrative, ecc.).
Entra in MyUnivr con le tue credenziali GIA.

Area riservata studenti


Graduation

List of theses and work experience proposals

theses proposals Research area
Analisi e percezione dei segnali biometrici per l'interazione con robot AI, Robotics & Automatic Control - AI, Robotics & Automatic Control
Integrazione del simulatore del robot Nao con Oculus Rift AI, Robotics & Automatic Control - AI, Robotics & Automatic Control
Domain Adaptation Computer Science and Informatics: Informatics and information systems, computer science, scientific computing, intelligent systems - Computer graphics, computer vision, multi media, computer games
Domain Adaptation Computer Science and Informatics: Informatics and information systems, computer science, scientific computing, intelligent systems - Machine learning, statistical data processing and applications using signal processing (e.g. speech, image, video)
BS or MS theses in automated reasoning Computing Methodologies - ARTIFICIAL INTELLIGENCE
Domain Adaptation Computing Methodologies - IMAGE PROCESSING AND COMPUTER VISION
Domain Adaptation Computing methodologies - Machine learning
Dati geografici Information Systems - INFORMATION SYSTEMS APPLICATIONS
Analisi e percezione dei segnali biometrici per l'interazione con robot Robotics - Robotics
Integrazione del simulatore del robot Nao con Oculus Rift Robotics - Robotics
BS or MS theses in automated reasoning Theory of computation - Logic
BS or MS theses in automated reasoning Theory of computation - Semantics and reasoning
Proposte di tesi/collaborazione/stage in Intelligenza Artificiale Applicata Various topics
Proposte di Tesi/Stage/Progetto nell'ambito delle basi di dati/sistemi informativi Various topics

University Language Centre - CLA


Further services

I servizi e le attività di orientamento sono pensati per fornire alle future matricole gli strumenti e le informazioni che consentano loro di compiere una scelta consapevole del corso di studi universitario.